39 citations · 42 across the 3 of their papers we have counts for
3 papers
cs.LG2021
Flood forecasting with machine learning models in an operational framework
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal +28
The operational flood forecasting system by Google was developed to provide accurate real-time flood warnings to agencies and the public, with a focus on riverine floods in large,…
cs.LG2020★ 39 cited
HydroNets: Leveraging River Structure for Hydrologic Modeling
Zach Moshe, Asher Metzger, Gal Elidan +3
Accurate and scalable hydrologic models are essential building blocks of several important applications, from water resource management to timely flood warnings. However, as the cl…
cs.LG2019★ 3 cited
Accurate Hydrologic Modeling Using Less Information
Guy Shalev, Ran El-Yaniv, Daniel Klotz +3
Joint models are a common and important tool in the intersection of machine learning and the physical sciences, particularly in contexts where real-world measurements are scarce. R…